Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

08:26:26 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.9 / v1.14.9-9-gcde0dcf)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.now(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

08:26:26 WARNING opendrift.models.shipdrift:180: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
08:26:26 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
08:26:30 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
08:26:30 INFO    opendrift.models.basemodel.environment:230:    horizontal_diffusivity: 100.000000
08:26:30 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
08:26:30 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
08:26:30 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_significant_height: 0.000000
08:26:30 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

08:26:30 INFO    opendrift:1839: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
08:26:30 INFO    opendrift:1839: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
08:26:30 INFO    opendrift:947: Using existing reader for land_binary_mask to move elements to ocean
08:26:30 INFO    opendrift:978: All points are in ocean
08:26:30 INFO    opendrift:2136: 2026-03-25 08:26:26.272919 - step 1 of 24 - 1000 active elements (0 deactivated)
08:26:30 INFO    opendrift.readers:64: Opening file with xr.open_dataset
08:26:32 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
08:26:32 INFO    opendrift.readers:64: Opening file with xr.open_dataset
08:26:33 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
08:26:33 INFO    opendrift.readers:64: Opening file with xr.open_dataset
08:26:35 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
08:26:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:39 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:39 INFO    opendrift:2136: 2026-03-25 09:26:26.272919 - step 2 of 24 - 1000 active elements (0 deactivated)
08:26:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:41 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:41 INFO    opendrift:2136: 2026-03-25 10:26:26.272919 - step 3 of 24 - 1000 active elements (0 deactivated)
08:26:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:42 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:42 INFO    opendrift:2136: 2026-03-25 11:26:26.272919 - step 4 of 24 - 1000 active elements (0 deactivated)
08:26:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:44 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:44 INFO    opendrift:2136: 2026-03-25 12:26:26.272919 - step 5 of 24 - 1000 active elements (0 deactivated)
08:26:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:46 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:46 INFO    opendrift:2136: 2026-03-25 13:26:26.272919 - step 6 of 24 - 1000 active elements (0 deactivated)
08:26:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:49 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:49 INFO    opendrift:2136: 2026-03-25 14:26:26.272919 - step 7 of 24 - 1000 active elements (0 deactivated)
08:26:51 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:51 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:51 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:51 INFO    opendrift:2136: 2026-03-25 15:26:26.272919 - step 8 of 24 - 1000 active elements (0 deactivated)
08:26:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:53 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:53 INFO    opendrift:2136: 2026-03-25 16:26:26.272919 - step 9 of 24 - 1000 active elements (0 deactivated)
08:26:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:56 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:26:56 INFO    opendrift:2136: 2026-03-25 17:26:26.272919 - step 10 of 24 - 1000 active elements (0 deactivated)
08:26:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:26:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:00 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:00 INFO    opendrift:2136: 2026-03-25 18:26:26.272919 - step 11 of 24 - 1000 active elements (0 deactivated)
08:27:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:02 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:02 INFO    opendrift:2136: 2026-03-25 19:26:26.272919 - step 12 of 24 - 1000 active elements (0 deactivated)
08:27:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:05 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:05 INFO    opendrift:2136: 2026-03-25 20:26:26.272919 - step 13 of 24 - 1000 active elements (0 deactivated)
08:27:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:08 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:08 INFO    opendrift:2136: 2026-03-25 21:26:26.272919 - step 14 of 24 - 1000 active elements (0 deactivated)
08:27:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:11 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:11 INFO    opendrift:2136: 2026-03-25 22:26:26.272919 - step 15 of 24 - 1000 active elements (0 deactivated)
08:27:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:13 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:13 INFO    opendrift:2136: 2026-03-25 23:26:26.272919 - step 16 of 24 - 1000 active elements (0 deactivated)
08:27:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:17 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:17 INFO    opendrift:2136: 2026-03-26 00:26:26.272919 - step 17 of 24 - 1000 active elements (0 deactivated)
08:27:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:19 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:19 INFO    opendrift:2136: 2026-03-26 01:26:26.272919 - step 18 of 24 - 1000 active elements (0 deactivated)
08:27:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:21 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:21 INFO    opendrift:2136: 2026-03-26 02:26:26.272919 - step 19 of 24 - 1000 active elements (0 deactivated)
08:27:23 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:23 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:24 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:24 INFO    opendrift:2136: 2026-03-26 03:26:26.272919 - step 20 of 24 - 1000 active elements (0 deactivated)
08:27:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:26 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:26 INFO    opendrift:2136: 2026-03-26 04:26:26.272919 - step 21 of 24 - 1000 active elements (0 deactivated)
08:27:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:29 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:29 INFO    opendrift:2136: 2026-03-26 05:26:26.272919 - step 22 of 24 - 1000 active elements (0 deactivated)
08:27:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:31 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:31 INFO    opendrift:2136: 2026-03-26 06:26:26.272919 - step 23 of 24 - 1000 active elements (0 deactivated)
08:27:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:35 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
08:27:35 INFO    opendrift:2136: 2026-03-26 07:26:26.272919 - step 24 of 24 - 1000 active elements (0 deactivated)
08:27:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
08:27:39 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 3MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/25)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    horizontal_diffusivity                                                               (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/98)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))

  • time
    (time)
    datetime64[ns]
    2026-03-25T08:26:26.272919 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2026-03-25T08:26:26.272919000', '2026-03-25T09:26:26.272919000',
           '2026-03-25T10:26:26.272919000', '2026-03-25T11:26:26.272919000',
           '2026-03-25T12:26:26.272919000', '2026-03-25T13:26:26.272919000',
           '2026-03-25T14:26:26.272919000', '2026-03-25T15:26:26.272919000',
           '2026-03-25T16:26:26.272919000', '2026-03-25T17:26:26.272919000',
           '2026-03-25T18:26:26.272919000', '2026-03-25T19:26:26.272919000',
           '2026-03-25T20:26:26.272919000', '2026-03-25T21:26:26.272919000',
           '2026-03-25T22:26:26.272919000', '2026-03-25T23:26:26.272919000',
           '2026-03-26T00:26:26.272919000', '2026-03-26T01:26:26.272919000',
           '2026-03-26T02:26:26.272919000', '2026-03-26T03:26:26.272919000',
           '2026-03-26T04:26:26.272919000', '2026-03-26T05:26:26.272919000',
           '2026-03-26T06:26:26.272919000', '2026-03-26T07:26:26.272919000',
           '2026-03-26T08:26:26.272919000'], dtype='datetime64[ns]')

• Data variables: (25)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          shape=(1000, 25), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 5.034 5.072 ... 5.511 5.535

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.938629

    maxval :

    6.0857654

    array([[5.0348186, 5.0337763, 5.072461 , ..., 5.751084 , 5.764632 ,
            5.769936 ],
           [5.007899 , 5.004702 , 5.061539 , ..., 5.623428 , 5.6212993,
            5.5790143],
           [5.0193124, 5.0449495, 5.0748477, ..., 5.9184046, 5.937039 ,
            5.9513283],
           ...,
           [5.0018587, 5.0243697, 5.0646586, ..., 5.7501783, 5.78353  ,
            5.7997465],
           [4.9773602, 4.9812737, 5.0074587, ..., 5.6437497, 5.681269 ,
            5.7288685],
           [4.9929357, 5.014662 , 5.0454855, ..., 5.5161853, 5.5114765,
            5.5347223]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.03 63.04 ... 62.63 62.6

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.50884

    maxval :

    63.1234

    array([[63.004982, 63.02979 , 63.03858 , ..., 62.68808 , 62.680164,
            62.65278 ],
           [63.008007, 63.03022 , 63.034832, ..., 62.638096, 62.620148,
            62.58938 ],
           [62.99621 , 63.011105, 63.009533, ..., 62.6691  , 62.662037,
            62.64878 ],
           ...,
           [63.001423, 63.01768 , 63.0241  , ..., 62.66509 , 62.62974 ,
            62.61334 ],
           [62.989754, 63.019493, 63.038227, ..., 62.805878, 62.775303,
            62.758312],
           [62.98824 , 63.00244 , 63.021225, ..., 62.64898 , 62.63149 ,
            62.60345 ]], shape=(1000, 25), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]],
          shape=(1000, 25), dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], shape=(1000, 25), dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], shape=(1000, 25), dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]],
          shape=(1000, 25), dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]],
          shape=(1000, 25), dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]],
          shape=(1000, 25), dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]],
          shape=(1000, 25), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    7.822 9.842 11.52 ... 9.633 9.633

    minval :

    -0.69201475

    maxval :

    17.872923

    array([[ 7.821662 ,  9.841703 , 11.522856 , ...,  2.9290347,  4.3805046,
             4.3805046],
           [ 6.810555 ,  8.248696 ,  7.8402004, ...,  6.5082912,  7.0573363,
             7.0573363],
           [ 8.126677 ,  8.265987 ,  9.692318 , ..., 11.889367 , 10.732919 ,
            10.732919 ],
           ...,
           [ 6.502036 ,  6.849043 ,  8.772845 , ..., 10.01118  , 11.798127 ,
            11.798127 ],
           [ 6.702186 ,  6.2511854,  7.3177524, ...,  7.1243167,  7.218967 ,
             7.218967 ],
           [ 5.263328 ,  5.961795 ,  6.2869434, ...,  8.820926 ,  9.632877 ,
             9.632877 ]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    0.7034 -4.613 ... -11.64 -11.64

    minval :

    -20.021814

    maxval :

    13.104977

    array([[  0.70340306,  -4.612808  ,  -5.473702  , ..., -13.018919  ,
            -13.223925  , -13.223925  ],
           [  9.751292  ,   1.0103432 ,  -0.36139965, ..., -12.031229  ,
            -10.3648405 , -10.3648405 ],
           [  5.7421455 ,  -0.44821763,  -0.78386134, ...,  -7.062789  ,
             -7.9190044 ,  -7.9190044 ],
           ...,
           [  8.457854  ,   2.62906   ,  -5.9018674 , ...,  -8.3203745 ,
             -6.6736455 ,  -6.6736455 ],
           [  8.306177  ,   5.598164  ,  -0.6636958 , ..., -13.589602  ,
            -13.362826  , -13.362826  ],
           [ 12.9621725 ,   9.589775  ,   5.0012927 , ..., -12.913322  ,
            -11.63668   , -11.63668   ]], shape=(1000, 25), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.07358 0.0462 ... -0.07604

    minval :

    -0.17195186

    maxval :

    0.16357298

    array([[ 0.0735779 ,  0.04619833,  0.04343201, ...,  0.00666349,
             0.00045276,  0.00045276],
           [ 0.07289786,  0.0452804 ,  0.0420257 , ..., -0.06037779,
            -0.08318008, -0.08318008],
           [ 0.07553115,  0.05769095,  0.0568508 , ..., -0.08928748,
            -0.11028512, -0.11028512],
           ...,
           [ 0.07792359,  0.055987  ,  0.05253366, ..., -0.02035522,
            -0.06716603, -0.06716603],
           [ 0.10089929,  0.07420019,  0.05421626, ..., -0.01002765,
            -0.00460087, -0.00460087],
           [ 0.08861796,  0.07057516,  0.05690584, ..., -0.06181432,
            -0.07604219, -0.07604219]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.2425 0.2568 ... -0.1232 -0.1232

    minval :

    -0.38834372

    maxval :

    0.30669674

    array([[ 0.24249467,  0.25681067,  0.22021787, ..., -0.0555975 ,
            -0.06600702, -0.06600702],
           [ 0.25850877,  0.27909315,  0.2324476 , ..., -0.1189234 ,
            -0.1365997 , -0.1365997 ],
           [ 0.23970726,  0.23057334,  0.19137773, ..., -0.04250044,
            -0.05424928, -0.05424928],
           ...,
           [ 0.255687  ,  0.2514933 ,  0.21591793, ..., -0.07867735,
            -0.11132138, -0.11132138],
           [ 0.24302243,  0.26660788,  0.27769607, ..., -0.21788065,
            -0.21136154, -0.21136154],
           [ 0.23670083,  0.23834239,  0.22982185, ..., -0.11057041,
            -0.12324212, -0.12324212]], shape=(1000, 25), dtype=float32)

  • horizontal_diffusivity
    (trajectory, time)
    float32
    100.0 100.0 100.0 ... 100.0 100.0

    minval :

    100.0

    maxval :

    100.0

    array([[100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           ...,
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.]],
          shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.1169 0.1172 ... 0.1034 0.1034

    minval :

    0.09552015

    maxval :

    0.31363446

    array([[0.11690813, 0.11721648, 0.14140311, ..., 0.11576021, 0.11065989,
            0.11065989],
           [0.11670294, 0.11827303, 0.14156118, ..., 0.10857188, 0.10167988,
            0.10167988],
           [0.11718479, 0.12035191, 0.14165166, ..., 0.11468809, 0.11056252,
            0.11056252],
           ...,
           [0.11737615, 0.12061823, 0.14223723, ..., 0.11339474, 0.10476181,
            0.10476181],
           [0.1197333 , 0.12374976, 0.14175506, ..., 0.11058972, 0.11153538,
            0.11153538],
           [0.11906525, 0.12376513, 0.1423724 , ..., 0.10853761, 0.10335528,
            0.10335528]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    0.08763 0.05991 ... -0.1894 -0.1894

    minval :

    -0.34935126

    maxval :

    0.089633144

    array([[ 0.08763208,  0.05991062,  0.01867512, ..., -0.17830575,
            -0.183377  , -0.183377  ],
           [ 0.08542784,  0.05852523,  0.01877064, ..., -0.18668696,
            -0.18898046, -0.18898046],
           [ 0.08635966,  0.05897016,  0.01661512, ..., -0.17808163,
            -0.18487673, -0.18487673],
           ...,
           [ 0.08486386,  0.05842535,  0.01790433, ..., -0.17746781,
            -0.1845307 , -0.1845307 ],
           [ 0.08014348,  0.0549238 ,  0.0206387 , ..., -0.20175052,
            -0.20483057, -0.20483057],
           [ 0.08212604,  0.05724021,  0.01824911, ..., -0.18875359,
            -0.18935032, -0.18935032]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    4.076 4.179 4.741 ... 5.427 5.427

    minval :

    4.0661755

    maxval :

    8.835266

    array([[4.076231 , 4.179434 , 4.741392 , ..., 5.2980337, 5.3134575,
            5.3134575],
           [4.0885253, 4.2021384, 4.7483616, ..., 5.3763304, 5.3552017,
            5.3552017],
           [4.08209  , 4.1584826, 4.676738 , ..., 5.099395 , 5.1370945,
            5.1370945],
           ...,
           [4.08944  , 4.181636 , 4.7343426, ..., 5.2826724, 5.190339 ,
            5.190339 ],
           [4.0868526, 4.2143974, 4.827571 , ..., 5.3754225, 5.4348574,
            5.4348574],
           [4.085007 , 4.182791 , 4.74811  , ..., 5.4109836, 5.4275   ,
            5.4275   ]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    7.627 7.959 8.395 ... 8.054 8.054

    minval :

    7.581873

    maxval :

    9.030858

    array([[7.62697  , 7.95881  , 8.39485  , ..., 7.949391 , 7.956487 ,
            7.956487 ],
           [7.656808 , 7.97946  , 8.400419 , ..., 8.0275955, 8.019819 ,
            8.019819 ],
           [7.6340256, 7.8973413, 8.334709 , ..., 7.860817 , 7.8726406,
            7.8726406],
           ...,
           [7.651183 , 7.9276543, 8.383186 , ..., 7.9681163, 7.9090753,
            7.9090753],
           [7.649716 , 7.9417973, 8.472855 , ..., 7.869976 , 7.9039574,
            7.9039574],
           [7.6408157, 7.893512 , 8.394772 , ..., 8.018696 , 8.053651 ,
            8.053651 ]], shape=(1000, 25), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2026-03-25 08:26:26.272919', '2026-03-25 09:26:26.272919',
                   '2026-03-25 10:26:26.272919', '2026-03-25 11:26:26.272919',
                   '2026-03-25 12:26:26.272919', '2026-03-25 13:26:26.272919',
                   '2026-03-25 14:26:26.272919', '2026-03-25 15:26:26.272919',
                   '2026-03-25 16:26:26.272919', '2026-03-25 17:26:26.272919',
                   '2026-03-25 18:26:26.272919', '2026-03-25 19:26:26.272919',
                   '2026-03-25 20:26:26.272919', '2026-03-25 21:26:26.272919',
                   '2026-03-25 22:26:26.272919', '2026-03-25 23:26:26.272919',
                   '2026-03-26 00:26:26.272919', '2026-03-26 01:26:26.272919',
                   '2026-03-26 02:26:26.272919', '2026-03-26 03:26:26.272919',
                   '2026-03-26 04:26:26.272919', '2026-03-26 05:26:26.272919',
                   '2026-03-26 06:26:26.272919', '2026-03-26 07:26:26.272919',
                   '2026-03-26 08:26:26.272919'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (98)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2026-03-25 08:26:30.460543

  date_created :

  2026-03-25T08:26:30.460556

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2026-03-25 08:26:26.272919

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:horizontal_diffusivity :

  None

  config_environment:fallback:horizontal_diffusivity :

  100

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.14.9

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2026-03-25 08:26:30.468647

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_horizontal_diffusivity :

  100

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2026-03-26 08:26:26.272919

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:01.7 total 0:00:00.0 preparing 0:00:01.7 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:16.9 total 0:00:00.0 preparing 0:00:16.9 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:25.4 total 0:00:00.0 preparing 0:00:25.3 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:19.7 total 0:00:00.0 preparing 0:00:19.6 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 1:14.8 total time 4.2 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:08.8 main loop 0.4 updating elements 1.7 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.50884

  geospatial_lat_max :

  63.1234

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.938629

  geospatial_lon_max :

  6.0857654

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:14.879596

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:01.7  total
 0:00:00.0  preparing
 0:00:01.7  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:16.9  total
 0:00:00.0  preparing
 0:00:16.9  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:25.4  total
 0:00:00.0  preparing
 0:00:25.3  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:19.7  total
 0:00:00.0  preparing
 0:00:19.6  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 1:14.8 total time
    4.2 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:08.8 main loop
      0.4 updating elements
    1.7 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.14.9)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
Readers not added for the following variables:
  horizontal_diffusivity

Discarded readers:

Time:
        Start: 2026-03-25 08:26:26.272919 UTC
        Present: 2026-03-26 08:26:26.272919 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

08:28:10 INFO    opendrift:4697: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
08:28:29 INFO    opendrift:3120: Time to make animation: 0:00:20.533835